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Detalle de: Synechocystis sp. PCC6803 metabolic models for the enhanced production of hydrogen

Title Synechocystis sp. PCC6803 metabolic models for the enhanced production of hydrogen
Abstract

In the present economy, difficulties to access energy sources are real drawbacks to maintain our current lifestyle. In fact, increasing interests have been gathered around efficient strategies to use energy sources that do not generate high CO2 titers. Thus, science-funding agencies have invested more resources into research on hydrogen among other biofuels as interesting energy vectors. This article reviews present energy challenges and frames it into the present fuel usage landscape. Different strategies for hydrogen production are explained and evaluated. Focus is on biological hydrogen production; fermentation and photon-fuelled hydrogen production are compared. Mathematical models in biology can be used to assess, explore and design production strategies for industrially relevant metabolites, such as biofuels. We assess the diverse construction and uses of genome-scale metabolic models of cyanobacterium Synechocystis sp. PCC6803 to efficiently obtain biofuels. This organism has been studied as a potential photon-fuelled production platform for its ability to grow from carbon dioxide, water and photons, on simple culture media. Finally, we review studies that propose production strategies to weigh this organism's viability as a biofuel production platform. Overall, the work presented in this review unveils the industrial capabilities of cyanobacterium Synechocystis sp. PCC6803 to evolve interesting metabolites as a clean biofuel production platform.

Apa Reference Montagud, A., Gamermann, D., Fernández de Córdoba, P., & Urchueguía, J. F. (2013). Synechocystissp. PCC6803 metabolic models for the enhanced production of hydrogen. Critical Reviews in Biotechnology, 35(2), 184–198. 10.3109/07388551.2013.829799
Doi 10.3109/07388551.2013.829799
Publication Date 3 Oct 2013
Publication Type Article
Researcher Arnau Montagud Aquino
Ontology Biosystems Modeling, Metabolic modelling
Research Groups Systems Biology Modeling
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